CN110151136B - Method, device, equipment and medium for monitoring sleep state of conditional reference heart rate - Google Patents
Method, device, equipment and medium for monitoring sleep state of conditional reference heart rate Download PDFInfo
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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Abstract
The invention discloses a method, a device, equipment and a medium for monitoring a sleep state of a conditional reference heart rate, wherein the method comprises the steps of collecting at least one axis acceleration variable quantity triggered by turning motion within a preset first time period; judging whether the suspected sleep state is entered according to the collected axial acceleration variation; if the suspected sleep state is entered, acquiring the heart rate within a preset second time period; and calculating the average heart rate, and if the average heart rate is lower than the target heart rate, judging to enter a sleep state. According to the invention, the suspected sleep state is judged by analyzing the axial acceleration variation, and then the heart rate detection is started, so that the heart rate detection is started only after the suspected sleep state is entered, and the sleep state or the low activity state is distinguished, thereby avoiding the long-time start of the heart rate acquisition state, and realizing accurate sleep monitoring.
Description
Technical Field
The invention relates to the technical field of map application, in particular to a method, a device, equipment and a medium for monitoring a sleep state of a conditional reference heart rate.
Background
The existing sleep condition detection methods include a polysomnography method, a pressure sensor-based detection method, an overturn-based detection method and the like. The polysomnography method is a 'gold standard' in the sleep detection method, and is used for acquiring physiological signals of a human body through various sensors and finally recording different patterns for analysis. The method can provide a plurality of physiological parameters of a tested person, but the used equipment is expensive and complex to operate and needs professional personnel to operate; meanwhile, the testee needs to stick various sensors on the body, and the psychological load influence brought by the sensors is large.
The sleep condition detection method based on the pressure sensor is used for carrying out sleep quality analysis by collecting vibration caused in the sleeping process of a human body through the pressure sensor. Although the method can not generate any physiological or psychological influence on the tested person, the arrangement position of the sensor can generate great influence on the measurement precision, and the method is only suitable for single person measurement.
The sleep condition detection method based on the turnover detection has the basic working principle that acceleration change data of each axis during turnover movement in the sleep process are collected through an acceleration sensor worn on an arm, and then calculation of corresponding algorithms is carried out on the obtained data to obtain sleep quality indexes. The method has the advantages of accurate measurement, simple operation and convenient wearing. However, the single sleep state detection method based on the roll-over detection is difficult to judge the sleep state of the user in a static state, for example, the user leans on a sofa to watch a television computer, the user lies on a bed to play a mobile phone, and the like, at this time, the data generated by the G-sensor is very similar to the data characteristics generated when the user sleeps, and it is difficult to distinguish whether the user actually sleeps.
Disclosure of Invention
In order to solve the technical problem that the sleep state or the low activity state is difficult to distinguish in the prior art, embodiments of the present invention provide a method, an apparatus, a device, and a medium for monitoring a sleep state of a conditional reference heart rate.
In one aspect, the invention provides a sleep state monitoring method with conditional reference to heart rate, the method comprising:
collecting at least one axis acceleration variation triggered by the overturning motion within a preset first time period;
judging whether the suspected sleep state is entered according to the collected axial acceleration variation;
if the suspected sleep state is entered, acquiring the heart rate within a preset second time period;
and calculating the average heart rate, and if the average heart rate is lower than the target heart rate, judging to enter a sleep state.
In another aspect, the present invention provides a sleep state monitoring device with conditional reference to heart rate, the device comprising:
the shaft acceleration variation module is used for acquiring at least one shaft acceleration variation triggered by the overturning motion within a preset first time period;
the suspected sleep state judging module is used for judging whether to enter a suspected sleep state according to the collected axial acceleration variation;
the heart rate acquisition module is used for acquiring the heart rate within a preset second time period if the suspected sleep state is entered;
and the judging module is used for calculating the average heart rate, and judging to enter a sleep state if the average heart rate is lower than the target heart rate.
In another aspect, the present invention provides an apparatus comprising a processor and a memory, the memory having stored therein at least one instruction, at least one program, set of codes, or set of instructions, the at least one instruction, the at least one program, set of codes, or set of instructions, loaded and executed by the processor to implement a sleep state monitoring method with conditional reference to a heart rate.
In another aspect, the present invention provides a computer storage medium having at least one instruction, at least one program, set of codes, or set of instructions stored therein, the at least one instruction, at least one program, set of codes, or set of instructions being loaded by a processor and executing a method for sleep state monitoring with conditional reference to heart rate.
The invention provides a sleep state monitoring method, a sleep state monitoring device, sleep state monitoring equipment and a sleep state monitoring medium with conditional reference to heart rate. According to the invention, the suspected sleep state is judged by analyzing the axial acceleration variation, and then the heart rate detection is started, so that the heart rate detection is started only after the suspected sleep state is entered, and the sleep state or the low activity state is distinguished, thereby avoiding the long-time start of the heart rate acquisition state, and realizing accurate sleep monitoring.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic illustration of an implementation environment provided by the present invention;
FIG. 2 is a flow chart of a sleep state monitoring method with conditional reference to heart rate according to the present invention;
FIG. 3 is a flowchart illustrating a method for determining whether to enter a suspected sleep state according to a collected axial acceleration variation according to the present invention;
FIG. 4 is a flow chart illustrating the present invention for analyzing the collected axial acceleration variation over the first time period to obtain the directed activity amount;
FIG. 5 is another flow chart illustrating the present invention for analyzing the acceleration variation of the shaft collected during the first time period to obtain the directed activity;
FIG. 6 is a schematic diagram of experimental effects of an embodiment of the present invention;
FIG. 7 is a block diagram of a sleep state monitoring device with conditional reference to heart rate according to the present invention;
fig. 8 is a hardware structural diagram of an apparatus for implementing the method provided by the embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to make the objects, technical solutions and advantages disclosed in the embodiments of the present invention more clearly apparent, the embodiments of the present invention are described in further detail below with reference to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the invention and are not intended to limit the embodiments of the invention.
Referring to fig. 1, the implementation environment includes: intelligent wearing equipment 01 and intelligent terminal 02. Intelligent wearing equipment 01 and intelligent terminal 02 communication connection.
Intelligent wearing equipment 01 can be for intelligent silver mirror, intelligent bracelet, intelligent wrist-watch, intelligent wrist strap, intelligent ring, intelligent clothing etc..
The intelligent terminal device 02 may include: the physical devices may also include software running in the physical devices, such as applications, and the like. For example, the intelligent terminal device 02 may operate a relevant management device of the intelligent wearable device 01.
The intelligent wearable device 01 completes the sleep state monitoring of the user wearing the intelligent wearable device 01 by acquiring the second information from the intelligent terminal device 02 and combining the first information acquired by the intelligent wearable device 01.
Referring to fig. 2, it shows a sleep state monitoring method with conditional reference to heart rate according to an embodiment of the present invention, which may be implemented by using an intelligent wearable device in the above implementation environment as an implementation subject, and the method includes:
s101, collecting at least one axis acceleration variation triggered by the overturning motion within a preset first time period.
Specifically, the acquisition of the axis acceleration variation can be realized through the G-sensor arranged in the intelligent wearable device. G-sensor (Accelerometer-sensor) chinese is an acceleration sensor that can sense changes in acceleration. When the force of the target object acting on the object in the acceleration process, such as various movement changes of shaking, falling, rising, falling and the like, can be converted into an electric signal by the G-sensor, and then the function with good program design can be completed after the calculation and analysis of the microprocessor.
The axis acceleration change amount may reflect the intensity of the motion of the user wearing the smart wearable device, that is, the activity amount thereof. If the amount of activity is large, it is evident that the user is awake, and if the amount of activity is small within the preset first time period, it is reasonable to suspect that the user is in a relatively quiet state, where the user may be doing a low activity, such as lying down to watch a cell phone or sitting to watch television, may be going to sleep, or may have gone to sleep.
The principle of the sleep condition detection method based on rollover detection in the prior art is just the same, and the user is presumed to enter the sleep state by the fact that the axis acceleration variation is small, but the user also has the possibility of performing low activity behavior, so that the presumption is failed, and the sleep monitoring precision is influenced. How to effectively distinguish low activity from sleep is also a common problem in the prior art.
And S103, judging whether the suspected sleep state is entered according to the collected axial acceleration variation.
Specifically, the determining whether to enter the suspected sleep state according to the collected axial acceleration variation includes, as shown in fig. 3:
and S1031, performing data analysis on the shaft acceleration variation acquired in the preset first time period to obtain the pointed activity amount.
In a possible embodiment, the G-sensor may acquire axis acceleration variation in three directions, i.e., an X axis, a Y axis, and a Z axis, and perform data analysis on the axis acceleration variation acquired in the preset first time period to obtain the activity directed to the axis acceleration variation, as shown in fig. 4, including:
s1, obtaining comprehensive variable quantity of each moment, wherein the comprehensive variable quantity is the root of the square sum of the axial acceleration variable quantities in the X axis direction, the Y axis direction and the Z axis direction.
And S3, acquiring a target comprehensive variation, wherein the target comprehensive variation is a comprehensive variation with a numerical value larger than a preset variation threshold.
And S5, adding the comprehensive variable quantity of each target in the preset first time period to obtain the activity.
In another possible embodiment, the frequency of activities may be further taken into account. The user has more frequent activities in the waking state, and the user has occasional activities such as turning over in the sleeping state, so the frequency degree of the activities and the intensity degree of the activities have significant significance for judging the sleeping. Specifically, the data analysis is performed on the axis acceleration variation acquired in the preset first time period to obtain the activity directed to the axis acceleration variation, as shown in fig. 5, the method includes:
and S2, acquiring comprehensive variable quantity of each moment, wherein the comprehensive variable quantity is the root of the square sum of the axial acceleration variable quantities in the X axis direction, the Y axis direction and the Z axis direction.
And S4, acquiring a target comprehensive variation, wherein the target comprehensive variation is a comprehensive variation with a numerical value larger than a preset variation threshold.
And S6, acquiring corresponding weight of the target comprehensive variation, wherein the weight reflects the user state near the occurrence moment of the target comprehensive variation.
The weight reflects the frequency of the user activity, and in one embodiment, the weight is obtained by:
calculating a reciprocal value corresponding to each target comprehensive variation, wherein the reciprocal value is the reciprocal of the difference between the acquisition time corresponding to the target comprehensive variation and the acquisition time corresponding to other target comprehensive variations which are nearest to the target comprehensive variation;
and normalizing each reciprocal value to obtain a weight value corresponding to each target comprehensive variable quantity.
And S8, carrying out weighted summation on the comprehensive variable quantity of each target in the preset first time period to obtain the activity.
S1033, judging whether the activity amount is smaller than an activity amount low-limit threshold value.
Specifically, the activity amount threshold may be set according to actual conditions, and may be related to or unrelated to user behavior habits.
And S1035, if the activity amount is smaller than the activity amount low-limit threshold, determining to enter a suspected sleep state.
And S105, if the suspected sleep state is entered, acquiring the heart rate within a preset second time period.
Specifically, whether the suspected sleep state is entered may be determined by determining a correspondence between the activity level and a preset activity level threshold, and if the activity level is smaller than the preset activity level threshold, the suspected sleep state may be determined to be entered.
In such a suspected sleep state, the user may perform a low activity or go to sleep.
To eliminate the interference caused by low activity behavior in suspected sleep states, a lot of experiments were performed in the embodiment of the present invention, please refer to fig. 6, which shows the experimental effect of the embodiment of the present invention. It is clear that a person's heart rate is significantly reduced after going to sleep relative to the heart rate in the awake state, and therefore disturbances caused by low activity activities can be excluded with reference to the heart rate in suspected sleep scenarios.
And S107, calculating an average heart rate, and if the average heart rate is lower than a target heart rate, judging to enter a sleep state.
Specifically, the target heart rate may be a lowest heart rate stored in a waking state of the user inside the smart wearable device. With the use of the heart rate acquisition function, the target heart rate may be updated according to the user's actual heart rate performance.
In one possible embodiment, after entering the sleep state, the heart rate acquisition function may be optionally turned off.
In another possible embodiment, if the average heart rate is higher than the target heart rate, the heart rate is continuously collected until the collection time reaches a preset time threshold or the sleep state is determined to be entered.
It should be noted that although there is a technology of using heart rate to perform sleep monitoring in the prior art, the power consumption is high when the heart rate detection is started, so that it is difficult to perform sleep monitoring based on heart rate for a long time, which also affects the implementation of the prior art of performing sleep monitoring based on heart rate, and this function also leads to reduced practicability and is difficult to meet the requirements of customers. According to the embodiment of the invention, the suspected sleep state is judged by analyzing the axial acceleration variation, and then the heart rate detection is started, so that the heart rate detection is started only after the suspected sleep state is entered, and the sleep state or the low activity state is distinguished, thereby avoiding the long-time start of the heart rate acquisition state, and realizing accurate sleep monitoring.
Further, still include:
and S109, if the sleep state is judged to be entered, acquiring a user operation instruction, or communicating with the intelligent terminal to acquire at least one judgment parameter.
And S1011, judging whether to enter a waking state according to the operation instruction or the judgment parameter.
In the prior art, the single G-sensor is used for judging whether a user is awake during sleep or not or is judged based on the heart rate, namely, the activity of the user is similar to that of the user who is asleep during the waking period of time, and the heart rate acquisition equipment is often in a closed state due to serious power consumption, so that the user cannot be monitored in time when entering the awake state. Through a large amount of user behavior habit related researches, the embodiment of the invention discovers that most users can operate hand rings or mobile phones when waking up. Therefore, the embodiment of the invention judges whether the user is awake by acquiring the user operation instruction or communicating with the intelligent terminal to acquire at least one judgment parameter.
Specifically, the user operation instruction may be any instruction for operating the intelligent wearable device, and the determination parameter may also point to any instruction for operating the intelligent terminal.
The sleep state monitoring method with the conditional reference heart rate disclosed by the embodiment of the invention can fully utilize the communication with the intelligent terminal, and improve the waking timeliness, so that the viscosity of a user is improved.
An embodiment of the present invention further provides a sleep state monitoring device with conditional reference to a heart rate, as shown in fig. 7, the device includes:
an axis acceleration variation module 201, configured to collect at least one axis acceleration variation triggered by the turning motion within a preset first time period;
the suspected sleep state judging module 203 is used for judging whether to enter a suspected sleep state according to the collected axis acceleration variation;
the heart rate acquisition module 205 is configured to acquire a heart rate within a preset second time period if the suspected sleep state is entered;
and the judging module 207 is used for calculating the average heart rate, and judging to enter a sleep state if the average heart rate is lower than the target heart rate.
Specifically, the embodiments of the sleep state monitoring device and the method for conditionally referring to the heart rate are all based on the same inventive concept.
The embodiment of the present invention further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing various steps of the sleep state monitoring method with conditional reference to a heart rate according to the embodiment of the present invention, which are not described herein again.
Further, fig. 8 shows a hardware structure diagram of an apparatus for implementing the method provided by the embodiment of the present invention, and the apparatus may participate in constituting or including the apparatus provided by the embodiment of the present invention. As shown in fig. 8, the device 10 may include one or more (shown as 102a, 102b, … …, 102 n) processors 102 (the processors 102 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. Besides, the method can also comprise the following steps: a display, an input/output interface (I/O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of the I/O interface), a network interface, a power source, and/or a camera. It will be understood by those skilled in the art that the structure shown in fig. 8 is only an illustration and is not intended to limit the structure of the electronic device. For example, device 10 may also include more or fewer components than shown in FIG. 8, or have a different configuration than shown in FIG. 8.
It should be noted that the one or more processors 102 and/or other data processing circuitry described above may be referred to generally herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part in software, hardware, firmware, or any combination thereof. Further, the data processing circuitry may be a single, stand-alone processing module, or incorporated in whole or in part into any of the other elements in the device 10 (or mobile device). As referred to in the embodiments of the application, the data processing circuit acts as a processor control (e.g. selection of a variable resistance termination path connected to the interface).
The memory 104 may be used to store software programs and modules of application software, such as program instructions/data storage devices corresponding to the methods described in the embodiments of the present invention, and the processor 102 executes various functional applications and data processing by executing the software programs and modules stored in the memory 104, so as to implement the sleep state monitoring method with conditional reference to heart rate described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory located remotely from processor 102, which may be connected to device 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of such networks may include wireless networks provided by the communication provider of the device 10. In one example, the transmission device 106 includes a network adapter (NIC) that can be connected to other network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 can be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
The display may be, for example, a touch screen type Liquid Crystal Display (LCD) that may enable a user to interact with a user interface of the device 10 (or mobile device).
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the device and server embodiments, since they are substantially similar to the method embodiments, the description is simple, and the relevant points can be referred to the partial description of the method embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (6)
1. A method of sleep state monitoring with conditional reference to heart rate, the method comprising: collecting at least one axis acceleration variation triggered by the overturning motion within a preset first time period;
acquiring comprehensive variable quantity of each moment according to the acquired axial acceleration variable quantity, wherein the comprehensive variable quantity is the root of the square sum of the axial acceleration variable quantities in the X axis direction, the Y axis direction and the Z axis direction;
acquiring a target comprehensive variation, wherein the target comprehensive variation is a comprehensive variation with a numerical value larger than a preset variation threshold;
acquiring the activity of a user, wherein the activity is a value obtained by performing weighted summation on each target comprehensive variation in the preset first time period, the weight of the target comprehensive variation reflects the user state near the occurrence moment of the target comprehensive variation, and the acquiring mode of the weight comprises the following steps: calculating a reciprocal value corresponding to each target comprehensive variable quantity, wherein the reciprocal value is the reciprocal of a difference value between the acquisition time corresponding to the target comprehensive variable quantity and the acquisition time corresponding to other target comprehensive variable quantities nearest to the target comprehensive variable quantity, and normalizing each reciprocal value to obtain a weight value corresponding to each target comprehensive variable quantity;
judging whether the activity amount is smaller than an activity amount minimum threshold, and if the activity amount is smaller than the activity amount minimum threshold, judging that a suspected sleep state is entered;
if the suspected sleep state is entered, acquiring the heart rate within a preset second time period;
and calculating the average heart rate, and if the average heart rate is lower than the target heart rate, judging to enter a sleep state.
2. The method of claim 1, comprising:
if the sleep state is judged to be entered, acquiring a user operation instruction, or communicating with the intelligent terminal to acquire at least one judgment parameter;
and judging whether to enter the waking state according to the operation instruction or the judgment parameter.
3. The method of claim 2, comprising:
the user operation instruction is any instruction for operating the intelligent wearable device, and the judgment parameter points to any instruction for operating the intelligent terminal.
4. Sleep state monitoring device with conditional reference to heart rate, characterized in that the device package
Comprises the following steps:
the shaft acceleration variation module is used for acquiring at least one shaft acceleration variation triggered by the overturning motion within a preset first time period;
the comprehensive variable acquiring module is used for acquiring comprehensive variable at each moment according to the acquired axial acceleration variable, wherein the comprehensive variable is the root of the square sum of the axial acceleration variable in the X-axis direction, the Y-axis direction and the Z-axis direction;
the target comprehensive variation obtaining module is used for obtaining a target comprehensive variation, and the target comprehensive variation is a comprehensive variation with a numerical value larger than a preset variation threshold;
the activity acquisition module is used for acquiring the activity of a user, wherein the activity is a value obtained by weighting and summing each target comprehensive variation in the preset first time period, the weight of the target comprehensive variation reflects the user state near the occurrence moment of the target comprehensive variation, and the acquisition mode of the weight comprises the following steps: calculating a reciprocal value corresponding to each target comprehensive variable quantity, wherein the reciprocal value is the reciprocal of a difference value between the acquisition time corresponding to the target comprehensive variable quantity and the acquisition time corresponding to other target comprehensive variable quantities nearest to the target comprehensive variable quantity, and normalizing each reciprocal value to obtain a weight value corresponding to each target comprehensive variable quantity;
a suspected sleep state judgment module, configured to judge whether the activity amount is smaller than an activity amount minimum threshold, and if the activity amount is smaller than the activity amount minimum threshold, determine to enter a suspected sleep state;
the heart rate acquisition module is used for acquiring the heart rate within a preset second time period if the suspected sleep state is entered;
and the judging module is used for calculating the average heart rate, and judging to enter a sleep state if the average heart rate is lower than the target heart rate.
5. A sleep state monitoring device with a conditional reference heart rate, the device comprising a processor and a memory, the memory having stored therein at least one instruction, at least one program, set of codes or set of instructions, the at least one instruction, the at least one program, set of codes or set of instructions being loaded and executed by the processor to implement a sleep state monitoring method with a conditional reference heart rate according to any of claims 1-3.
6. A computer storage medium having stored therein at least one instruction, at least one program, set of codes, or set of instructions, which is loaded by a processor and which performs a method of sleep state monitoring with conditional reference to heart rate according to any of claims 1-3.
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| CN110710962A (en) * | 2019-11-08 | 2020-01-21 | 北京卡路里信息技术有限公司 | Sleep state detection method and device |
| CN113495609A (en) * | 2020-04-01 | 2021-10-12 | 华为技术有限公司 | Sleep state judgment method and system, wearable device and storage medium |
| CN111839465A (en) * | 2020-07-30 | 2020-10-30 | 歌尔科技有限公司 | Sleep detection method and device, intelligent wearable device and readable storage medium |
| CN112401838B (en) * | 2020-11-16 | 2023-07-14 | 上海创功通讯技术有限公司 | Method for detecting sleep state by wearable device and wearable device |
| CN117481614A (en) * | 2023-12-26 | 2024-02-02 | 荣耀终端有限公司 | Sleep state detection method and related equipment |
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